Abstract:
According to the characteristics of order picking, taking the shortest operating time as the goal, this paper constructs the corresponding optimization mathematical model. By introducing antibody extraction and injection based on Partheno Genetic Algorithm(PGA), Immune Partheno Genetic Algorithm(IPGA) is designed to gain the optimal solution. Simulation results prove that the algorithm has better global search capability, high convergence speed and short response time, which reduces the stacker operating time and improves the working efficiency of Automated Storage and Retrieval System(AS/RS).
Key words:
Automated Storage and Retrieval System(AS/RS),
picking operation,
gene recombination,
Immune Partheno Genetic Algorithm (IPGA),
immune antibody
摘要： 根据堆垛机拣选作业的特点，以最短作业时间为目标构建优化数学模型。在单亲遗传算法的基础上引入免疫抗体的提取与注射机制，设计一种免疫单亲遗传算法用于求取模型最优解。仿真结果证明，该算法具备全局搜索能力，收敛速度快，响应时间短，可有效减少堆垛机的作业时间，提高自动化立体仓库的存取效率。
关键词:
自动化立体仓库,
拣选作业,
基因重组,
免疫单亲遗传算法,
免疫抗体
CLC Number:
HUANG Yang-Bei, LIU Mo-Jun, DING Feng, LIU Hui. Optimization of Picking Operation Based on Immune Partheno Genetic Algorithm[J]. Computer Engineering, 2011, 37(11): 206-208,211.
黄杨波, 刘万军, 丁鹏, 刘卉. 基于免疫单亲遗传算法的拣选作业优化[J]. 计算机工程, 2011, 37(11): 206-208,211.